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[movies]MIT15.084JS04 - MIT OpenCourseWare
This course introduces students to the fundamentals of nonlinear optimization theory and methods. Topics include unconstrained and constrained optimization, linear and quadratic programming, Lagrange and conic duality theory, interior-point algorithms and theory, Lagrangian relaxation, generalized programming, and semi-definite programming. Algorithmic methods used in the class include steepest descent, Newton's method, conditional gradient and subgradient optimization, interior-point methods an...
Keywords: unconstrained and constrained optimization; unconstrained and constrained optimization; Lagrangean relaxation; generalized programming; Newton's method; conditional gradient and subgradient optimization; linear and quadratic programming; lagrange and conic duality theory; interior-point algorithms and theory; semi-definite programming; Algorithmic methods include steepest descent; interior-point methods and penalty and barrier methods; 15.084J; 6.252J; 15.084; 6.252
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